Numerical Solution of Piecewise Constant Delay Systems Based on a Hybrid Framework

An efficient numerical scheme for solving delay differential equations with a piecewise constant delay function is developed in this paper. The proposed approach is based on a hybrid of block-pulse functions and Taylor’s polynomials. The operational matrix of delay corresponding to the proposed hybrid functions is introduced. The sparsity of this matrix significantly reduces the computation time and memory requirement. The operational matrices of integration, delay, and product are employed to transform the problem under consideration into a system of algebraic equations. It is shown that the developed approach is also applicable to a special class of nonlinear piecewise constant delay differential equations. Several numerical experiments are examined to verify the validity and applicability of the presented technique

Factors Associated With Intraventricular Hemorrhage in Very Low Birth Weight Neonates in Mousavi Hospital in Zanjan in 2012-2013

Background: Intraventricular hemorrhage (IVH) is one of the most important causes of cognitive and motor disorder in children with very low birth weight and is associated with high mortality and disability rate. Objectives: The aim of this study was to determine IVH risk factors in the first days of life in neonates weighing less than 1500g (VLBW) so that the results can contribute to the improvement of the therapeutic function of the delivery room and ultimately IVH risk prevention. Methods: This descriptive study was conducted on 110 VLBW neonates who were admitted to the hospital affiliated to Zanjan University of Medical Sciences during the years 2012-2013 Zanjan-Iran. Parameters including gender, birth weight, birth Apgar, regimens, and type of delivery were recorded in the questionnaire and data analysis was conducted using Chi-square test in SPSS. Results: From 110 studied neonates, 21(19%) had IVH, of which 11(52%), 5(23.8%) and 5(23.8%) suffered from Grade I, II and III IVH, respectively. Meanwhile, among the studied variables, recovery steps were taken in the delivery room in the IVH group. The cranial ultrasonography was carried out for these neonates in the first 72 h of birth and they were categorized as Grade one to four, based on evidence of brain hemorrhage. There was a significant difference between maternity and infant information and without IVH; but it was not statistically significant. Conclusion: According to the present study, the recovery process seemed to be a risk factor for the incidence of IVH in neonates; therefore, the health level of neonates can be improved by optimizing the mentioned process and reducing this risk factor

Using machine learning in prediction of ICU admission, mortality, and length of stay in the early stage of admission of COVID-19 patients

The recent COVID-19 pandemic has affected health systems across the world. Especially, Intensive Care Units (ICUs) have played a pivotal role in the treatment of critically-ill patients. At the same time however, the increasing number of admissions due to the vast prevalence of the virus have caused several problems for ICU wards such as overburdening of staff and shortages of medical resources. These issues might have affected the quality of healthcare services provided directly impacting a patient’s survival. The objective of this research is to leverage Machine Learning (ML) on hospital data in order to support hospital managers and practitioners with the treatment of COVID-19 patients. This is accomplished by providing more detailed inference about a patient’s likelihood of ICU admission, mortality and in case of hospitalization the length of stay (LOS). In this pursuit, the outcome variables are in three separate models predicted by five different ML algorithms: eXtreme Gradient Boosting (XGB), K-Nearest Neighbor (KNN), Random Forest (RF), bagged-CART (b-CART), and LogitBoost (LB). With the exception of KNN, the studied models show good predictive capabilities when evaluating relevant accuracy scores, such as area under the curve. By implementing an ensemble stacking approach (either a Neural Net or a General Linear Model) on top of the aforementioned ML algorithms the performance is further boosted. Ultimately, for the prediction of admission to the ICU, the ensemble stacking via a Neural Net achieved the best result with an accuracy of over 95%. For mortality at the ICU, the vanilla XGB performed slightly better (1% difference with the meta-model). To predict large length of stays both ensemble stacking approaches yield comparable results. Besides it direct implications for managing COVID-19 patients, the approach presented serves as an example how data can be employed in future pandemics or crises

Applications of different machine learning approaches in prediction of breast cancer diagnosis delay

Background: The increasing rate of breast cancer (BC) incidence and mortality in Iran has turned this disease into a challenge. A delay in diagnosis leads to more advanced stages of BC and a lower chance of survival, which makes this cancer even more fatal. Objectives: The present study was aimed at identifying the predicting factors for delayed BC diagnosis in women in Iran.Methods: In this study, four machine learning methods, including extreme gradient boosting (XGBoost), random forest (RF), neural networks (NNs), and logistic regression (LR), were applied to analyze the data of 630 women with confirmed BC. Also, different statistical methods, including chi-square, p-value, sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC), were utilized in different steps of the survey.Results: Thirty percent of patients had a delayed BC diagnosis. Of all the patients with delayed diagnoses, 88.5% were married, 72.1% had an urban residency, and 84.8% had health insurance. The top three important factors in the RF model were urban residency (12.04), breast disease history (11.58), and other comorbidities (10.72). In the XGBoost, urban residency (17.54), having other comorbidities (17.14), and age at first childbirth (>30) (13.13) were the top factors; in the LR model, having other comorbidities (49.41), older age at first childbirth (82.57), and being nulliparous (44.19) were the top factors. Finally, in the NN, it was found that being married (50.05), having a marriage age above 30 (18.03), and having other breast disease history (15.83) were the main predicting factors for a delayed BC diagnosis.Conclusion: Machine learning techniques suggest that women with an urban residency who got married or had their first child at an age older than 30 and those without children are at a higher risk of diagnosis delay. It is necessary to educate them about BC risk factors, symptoms, and self-breast examination to shorten the delay in diagnosis

Neuroprotective Effects of Bone Marrow Mesenchymal Stem Cells on Bilateral Common Carotid Arteries Occlusion Model of Cerebral Ischemia in Rat

Cell therapy is the most advanced treatment of the cerebral ischemia, nowadays. Herein, we discuss the neuroprotective effects of bone marrow mesenchymal stem cells (BMSCs) on rat hippocampal cells following intravenous injection of these cells in an ischemia-reperfusion model. Adult male Wistar rats were divided into 5 groups: control, sham (surgery without blockage of common carotid arteries), ischemia (common carotid arteries were blocked for 30 min prior to reperfusion), vehicle (7 days after ischemia PBS was injected via the tail vein), and treatment (injections of BMSC into the tail veins 7 days after ischemia). We performed neuromuscular and vestibulomotor function tests to assess behavioral function and, finally, brains were subjected to hematoxylin and eosin (H&E), anti-Brdu immunohistochemistry, and TUNEL staining. The ischemia group had severe apoptosis. The group treated with BMSCs had a lower mortality rate and also had significant improvement in functional recovery (P<0.001). Ischemia-reperfusion for 30 min causes damage and extensive neuronal death in the hippocampus, especially in CA1 and CA3 regions, leading to several functional and neurological deficits. In conclusion, intravenous injection of BMSCs can significantly decrease the number of apoptotic neurons and significantly improve functional recovery, which may be a beneficial treatment method for ischemic injuries. © 2016 Bagher Pourheydar et al

Design of a high-speed germanium-tin absorption modulator at mid-infrared wavelengths

We propose a high-speed electro-absorption modulator based on a direct bandgap Ge0.875Sn0.125 alloy operating at mid-infrared wavelengths. Enhancement of the Franz-Keldysh-effect by confinement of the applied electric field to GeSn in a reverse-biased junction results in 3.2dB insertion losses, a 35GHz bandwidth and a 6dB extinction ratio for a 2Vpp drive signal

Changes in Selected Organic and Inorganic Compounds in the Hydrothermal Carbonization Process Liquid While in Storage

Although many studies have investigated the hydrothermal transformation of feedstock biomass, little is known about the stability of the compounds present in the process liquid after the carbonization process is completed. The physicochemical characteristics of hydrothermal carbonization (HTC) liquid products may change over storage time, diminishing the amount of desired products or producing unwanted contaminants. These changes may restrict the use of HTC liquid products. Here, we investigate the effect of storage temperature (20, 4, and −18 °C) and time (weeks 1-12) on structural and compositional changes of selected organic compounds and physicochemical characteristics of the process liquid from the HTC of digested cow manure. ANOVA showed that the storage time has a significant effect on the concentrations of almost all of the selected organic compounds, except acetic acid. Considerable changes in the composition of the process liquid took place at all studied temperatures, including deep freezing at −18 °C. Prominent is the polymerization of aromatic compounds with the formation of precipitates, which settle over time. This, in turn, influences the inorganic compounds present in the liquid phase by chelating or selectively adsorbing them. The implications of these results on the further processing of the process liquid for various applications are discussed

One-loop Vilkovisky-DeWitt Counterterms for 2D Gravity plus Scalar Field Theory

The divergent part of the one-loop off-shell effective action is computed for a single scalar field coupled to the Ricci curvature of 2D gravity ($c \phi R$), and self interacting by an arbitrary potential term $V(\phi)$. The Vilkovisky-DeWitt effective action is used to compute gauge-fixing independent results. In our background field/covariant gauge we find that the Liouville theory is finite on shell. Off-shell, we find a large class of renormalizable potentials which include the Liouville potential. We also find that for backgrounds satisfying $R=0$, the Liouville theory is finite off shell, as well.Comment: 19 pages, OKHEP 92-00

Alteration of the dopamine receptors� expression in the cerebellum of the lysosomal acid phosphatase 2 mutant (Naked�ataxia (nax)) mouse

A spontaneous mutation in the lysosomal acid phosphatase (Acp2) enzyme (nax: Naked� ataxia) in experimental mice results in delayed hair appearance and severe cytoarchitectural impairments of the cerebellum, such as a Purkinje cell (PC) migration defect. In our previous investigation, our team showed that Acp2 expression plans a significant role in cerebellar development. On the other hand, the dopaminergic system is also a player in central nervous system (CNS) development, including cerebellar structure and function. In the current investigation, we have explored how Acp2 can be involved in the regulation of the dopaminergic pathway in the cerebellum via the regulation of dopamine receptor expression and patterning. We provided evidence about the distribution of different dopamine receptors in the developing cerebellum by comparing the expression of dopamine receptors on postnatal days (P) 5 and 17 between nax mice and wild�type (wt) littermates. To this aim, immunohistochemistry and Western blot analysis were conducted using five antibodies against dopamine receptors (DRD1, �2, �3, �4, and �5) accompanied by RNAseq data. Our results revealed that DRD1, �3, and �4 gene expressions significantly increased in nax cerebella but not in wt, while gene expressions of all 5 receptors were evident in PCs of both wt and nax cerebella. DRD3 was strongly expressed in the PCs� somata and cerebellar nuclei neurons at P17 in nax mice, which was comparable to the expression levels in the cerebella of wt littermates. In addition, DRD3 was expressed in scattered cells in a granular layer reminiscent of Golgi cells and was observed in the wt cerebella but not in nax mice. DRD4 was expressed in a subset of PCs and appeared to align with the unique parasagittal stripes pattern. This study contributes to our understanding of alterations in the expression pattern of DRDs in the cerebellum of nax mice in comparison to their wt littermates, and it highlights the role of Acp2 in regulating the dopaminergic system. © 2020 by the authors. Licensee MDPI, Basel, Switzerland